It turns out that MacOS Tahoe can generate and use secure-enclave backed SSH keys! This replaces projects like https://github.com/maxgoedjen/secretive

There is a shared library /usr/lib/ssh-keychain.dylib that traditionally has been used to add smartcard support to ssh by implementing PKCS11Provider interface. However since recently it also implements SecurityKeyProivder which supports loading keys directly from the secure enclave! SecurityKeyProvider is what is normally used to talk to FIDO2 devices (e.g. libfido2 can be used to talk to your Yubikey). However you can now use it to talk to your Secure Enclave instead!

A pattern for building personal knowledge bases using LLMs.

This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.

Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.

Passo a passo rápido pra instalar o Pi agent com DeepSeek, RTK e extensões.

npm install -g --ignore-scripts @earendil-works/pi-coding-agent

Production-ready ASR + Speaker Diarization using NVIDIA NeMo.

1. Model Architecture: Parakeet-TDT uses FastConformer (not Whisper's attention-heavy encoder)
2. Native Pipelines: The YAML config triggers optimized C++/CUDA code for VAD and clustering
3. TitaNet Embeddings: Much faster than x-vector or ECAPA-TDNN for speaker separation
4. BF16 Inference: ~30% VRAM savings on Ada Lovelace GPUs (RTX 4000/4090)